>>Hello, everyone. Welcome to the cubes presentation of the 80, but startup showcases MarTech is the focus. And this is all about the emerging cloud scale customer experience. This is season two, episode three of the ongoing series covering the exciting, fast growing startups from the cloud AWS ecosystem to talk about the future and what's available now, where are the actions? I'm your host John fur. Today. We joined by Cub alumni, Jerry Chen partner at Greylock ventures. Jerry. Great to see you. Thanks for coming on, >>John. Thanks for having me back. I appreciate you welcome there for season two. Uh, as a, as a guest star, >><laugh>, you know, Hey, you know, season two, it's not a one and done it's continued coverage. We, we got the episodic, uh, cube flicks model going >>Here. Well, you know, congratulations, the, the coverage on this ecosystem around AWS has been impressive, right? I think you and I have talked a long time about AWS and the ecosystem building. It just continues to grow. And so the coverage you did last season, all the events of this season is, is pretty amazing from the data security to now marketing. So it's, it's great to >>Watch. And 12 years now, the cube been running. I remember 2013, when we first met you in the cube, we just left VMware just getting into the venture business. And we were just riffing the next 80. No one really kind of knew how big it would be. Um, but we were kinda riffing on. We kind of had a sense now it's happening. So now you start to see every vertical kind of explode with the right digital transformation and disruption where you see new incumbents. I mean, new Newton brands get replaced the incumbent old guard. And now in MarTech, it's ripe for, for disruption because web two has gone on to web 2.5, 3, 4, 5, um, cookies are going away. You've got more governance and privacy challenges. There's a slew of kind of ad tech baggage, but yet lots of new data opportunities. Jerry, this is a huge, uh, thing. What's your take on this whole MarTech cloud scale, uh, >>Market? I, I think, I think to your point, John, that first the trends are correct and the bad and the good or good old days, the battle days MarTech is really about your webpage. And then email right there. There's, there's the emails, the only channel and the webpage was only real estate and technology to care about fast forward, you know, 10 years you have webpages, mobile apps, VR experiences, car experiences, your, your, your Alexa home experiences. Let's not even get to web three web 18, whatever it is. Plus you got text messages, WhatsApp, messenger, email, still great, et cetera. So I think what we've seen is both, um, explosion and data, uh, explosion of channel. So sources of data have increases and the fruits of the data where you can reach your customers from text, email, phone calls, etcetera have exploded too. So the previous generation created big company responses, Equa, you know, that exact target that got acquired by Oracle or, or, um, Salesforce, and then companies like, um, you know, MailChimp that got acquired as well, but into it, you're seeing a new generation companies for this new stack. So I, I think it's exciting. >>Yeah. And you mentioned all those things about the different channels and stuff, but the key point is now the generation shifts going on, not just technical generation, uh, and platform and tools, it's the people they're younger. They don't do email. They have, you know, proton mail accounts, zillion Gmail accounts, just to get the freebie. Um, they're like, they're, they'll do subscriptions, but not a lot. So the generational piece on the human side is huge. Okay. And then you got the standards, bodies thrown away, things like cookies. Sure. So all this is makes it for a complicated, messy situation. Um, so out of this has to come a billion dollar startup in my mind, >>I, I think multiple billion dollars, but I think you're right in the sense that how we want engage with the company branch, either consumer brands or business brands, no one wants to pick a phone anymore. Right? Everybody wants to either chat or DM people on Twitter. So number one, the, the way we engage is different, both, um, where both, how like chat or phone, but where like mobile device, but also when it's the moment when we need to talk to a company or brand be it at the store, um, when I'm shopping in real life or in my car or at the airport, like we want to reach the brands, the brands wanna reach us at the point of decision, the point of support, the point of contact. And then you, you layer upon that the, the playing field, John of privacy security, right? All these data silos in the cloud, the, the, the, the game has changed and become even more complicated with the startup. So the startups are gonna win. Will do, you know, the collect, all the data, make us secure in private, but then reach your customers when and where they want and how they want it. >>So I gotta ask you, because you had a great podcast just this week, published and snowflake had their event going on the data cloud, there's a new kind of SAS platform vibe going on. You're starting to see it play out. Uh, and one of the things I, I noticed on your podcast with the president of Hashi Corp, who was on people should listen to that podcast. It's on gray matter, which is the Greylocks podcast, uh, plug for you guys. He mentioned he mentions the open source dynamic, right? Sure. And, and I like what he, things, he said, he said, software business has changed forever. It's my words. Now he said infrastructure, but I'm saying software in general, more broader infrastructure and software as a category is all open source. One game over no debate. Right. You agree? >>I, I think you said infrastructure specifically starts at open source, but I would say all open source is one more or less because open source is in every bit of software. Right? And so from your operating system to your car, to your mobile phone, open source, not necessarily as a business model or, or, or whatever, we can talk about that. But open source as a way to build software distribute, software consume software has one, right? It is everywhere. So regardless how you make money on it, how you build software, an open source community ha has >>One. Okay. So let's just agree. That's cool. I agree with that. Let's take it to the next level. I'm a company starting a company to sell to big companies who pay. I gotta have a proprietary advantage. There's gotta be a way. And there is, I know you've talked about it, but I have my opinion. There is needs to be a way to be proprietary in a way that allows for that growth, whether it's integration, it's not gonna be on software license or maybe support or new open source model. But how does startups in the MarTech this area in general, when they disrupt or change the category, they gotta get value creation going. What's your take on, on building. >>You can still build proprietary software on top of open source, right? So there's many companies out there, um, you know, in a company called rock set, they've heavily open source technology like Rock's DB under the hood, but they're running a cloud database. That's proprietary snowflake. You talk about them today. You know, it's not open source technology company, but they use open source software. I'm sure in the hoods, but then there's open source companies, data break. So let's not confus the two, you can still build proprietary software. There's just components of open source, wherever we go. So number one is you can still build proprietary IP. Number two, you can get proprietary data sources, right? So I think increasingly you're seeing companies fight. I call this systems intelligence, right, by getting proprietary data, to train your algorithms, to train your recommendations, to train your applications, you can still collect data, um, that other competitors don't have. >>And then it can use the data differently, right? The system of intelligence. And then when you apply the system intelligence to the end user, you can create value, right? And ultimately, especially marketing tech, the highest level, what we call the system of engagement, right? If, if the chat bot the mobile UI, the phone, the voice app, etcetera, if you own the system of engagement, be a slack, or be it, the operating system for a phone, you can also win. So still multiple levels to play John in multiple ways to build proprietary advantage. Um, just gotta own system record. Yeah. System intelligence, system engagement. Easy, right? Yeah. >>Oh, so easy. Well, the good news is the cloud scale and the CapEx funded there. I mean, look at Amazon, they've got a ton of open storage. You mentioned snowflake, but they're getting a proprietary value. P so I need to ask you MarTech in particular, that means it's a data business, which you, you pointed out and we agree. MarTech will be about the data of the workflows. How do you get those workflows what's changing and how these companies are gonna be building? What's your take on it? Because it's gonna be one of those things where it might be the innovation on a source of data, or how you handle two parties, ex handling encrypted data sets. I don't know. Maybe it's a special encryption tool, so we don't know what it is. What's your what's, what's your outlook on this area? >>I, I, I think that last point just said is super interesting, super genius. It's integration or multiple data sources. So I think either one, if it's a data business, do you have proprietary data? Um, one number two with the data you do have proprietary, not how do you enrich the data and do you enrich the data with, uh, a public data set or a party data set? So this could be cookies. It could be done in Brad street or zoom info information. How do you enrich the data? Number three, do you have machine learning models or some other IP that once you collected the data, enriched the data, you know, what do you do with the data? And then number four is once you have, um, you know, that model of the data, the customer or the business, what do you deal with it? Do you email, do you do a tax? >>Do you do a campaign? Do you upsell? Do you change the price dynamically in our customers? Do you serve a new content on your website? So I think that workflow to your point is you can start from the same place, what to do with the data in between and all the, on the out the side of this, this pipeline is where a MarTech company can have then. So like I said before, it was a website to an email go to website. You know, we have a cookie fill out a form. Yeah. I send you an email later. I think now you, you can't just do a website to email, it's a website plus mobile apps, plus, you know, in real world interaction to text message, chat, phone, call Twitter, a whatever, you know, it's >>Like, it's like, they're playing checkers in web two and you're talking 3d chess. <laugh>, I mean, there's a level, there's a huge gap between what's coming. And this is kind of interesting because now you mentioned, you know, uh, machine learning and data, and AI is gonna factor into all this. You mentioned, uh, you know, rock set. One of your portfolios has under the hood, you know, open source and then use proprietary data and cloud. Okay. That's a configuration, that's an architecture, right? So architecture will be important in terms of how companies posture in this market, cuz MarTech is ripe for innovation because it's based on these old technologies, but there's tons of workflows, but you gotta have the data. Right. And so if I have the best journey map from a client that goes to a website, but then they go and they do something in the organic or somewhere else. If I don't have that, what good is it? It's like a blind spot. >>Correct. So I think you're seeing folks with the data BS, snowflake or data bricks, or an Amazon that S three say, Hey, come to my data cloud. Right. Which, you know, Snowflake's advertising, Amazon will say the data cloud is S3 because all your data exists there anyway. So you just, you know, live on S3 data. Bricks will say, S3 is great, but only use Amazon tools use data bricks. Right. And then, but on top of that, but then you had our SaaS companies like Oracle, Salesforce, whoever, and say, you know, use our qua Marketo, exact target, you know, application as a system record. And so I think you're gonna have a battle between, do I just work my data in S3 or where my data exists or gonna work my data, some other application, like a Marketo Ella cloud Z target, um, or, you know, it could be a Twilio segment, right. Was combination. So you'll have this battle between these, these, these giants in the cloud, easy, the castles, right. Versus, uh, the, the, the, the contenders or the, or the challengers as we call >>'em. Well, great. Always chat with the other. We always talk about castles in the cloud, which is your work that you guys put out, just an update on. So check out greylock.com. They have castles on the cloud, which is a great thesis on and a map by the way ecosystem. So you guys do a really good job props to Jerry and the team over at Greylock. Um, okay. Now I gotta ask kind of like the VC private equity sure. Market question, you know, evaluations. Uh, first of all, I think it's a great time to do a startup. So it's a good time to be in the VC business. I think the next two years, you're gonna find some nice gems, but also you gotta have that cleansing period. You got a lot of overvaluation. So what happened with the markets? So there's gonna be a lot of M and a. So the question is what are some of the things that you see as challenges for product teams in particular that might have that killer answer in MarTech, or might not have the runway if there's no cash, um, how do people partner in this modern era, cuz scale's a big deal, right? Mm-hmm <affirmative> you can measure everything. So you get the combination of a, a new kind of M and a market coming, a potential growth market for the right solution. Again, value's gotta be be there. What's your take on this market? >>I, I, I think you're right. Either you need runway, so cash to make it through, through this next, you know, two, three years, whatever you think the market Turmo is or two, you need scale, right? So if you're at a company of scale and you have enough data, you can probably succeed on your own. If not, if you're kind of in between or early to your point, either one focus, a narrower wedge, John, just like we say, just reduce the surface area. And next two years focus on solving one problem. Very, very well, or number two in this MarTech space, especially there's a lot of partnership and integration opportunities to create a complete solution together, to compete against kind of the incumbents. Right? So I think they're folks with the data, they're folks doing data, privacy, security, they're post focusing their workflow or marketing workflows. You're gonna see either one, um, some M and a, but I definitely can see a lot of Coopers in partnership. And so in the past, maybe you would say, I'm just raise another a hundred million dollars and do what you're doing today. You might say, look, instead of raising more money let's partner together or, or merge or find a solution. So I think people are gonna get creative. Yeah. Like said scarcity often is good. Yeah. I think forces a lot more focus and a lot more creativity. >>Yeah. That's a great point. I'm glad you brought that up up. Cause I didn't think you were gonna go there. I was gonna ask that biz dev activity is going to be really fundamental because runway combined with the fact that, Hey, you know, if you know, get real or you're gonna go under is a real issue. So now people become friends. They're like, okay, if we partner, um, it's clearly a good way to go if you can get there. So what advice would you give companies? Um, even most experienced, uh, founders and operators. This is a different market, right? It's a different kind of velocity, obviously architectural data. You mentioned some of those key things. What's the posture to partner. What's your advice? What's the combat man manual to kind of compete in this new biz dev world where some it's a make or break time, either get the funding, get the customers, which is how you get funding or you get a biz dev deal where you combine forces, uh, go to market together or not. What's your advice? >>I, I think that the combat manual is either you're partnering for one or two things, either one technology or two customers or sometimes both. So it would say which partnerships, youre doing for technology EG solution completers. Like you have, you know, this puzzle piece, I have this puzzle piece data and data privacy and let's work together. Um, or number two is like, who can help you with customers? And that's either a, I, they can be channel for you or, or vice versa or can share customers and you can actually go to market together and find customers jointly. So ideally you're partner for one, if not the other, sometimes both. And just figure out where in your life cycle do you need? Um, friends. >>Yeah. Great. My final question, Jerry, first of all, thanks for coming on and sharing your in insight as usual. Always. Awesome final question for the folks watching that are gonna be partnering and buying product and services from these startups. Um, there's a select few great ones here and obviously every other episode as well, and you've got a bunch you're investing in this, it's actually a good market for the ones that are lean companies that are lean and mean have value. And the cloud scale does provide that. So a lot of companies are getting it right, they're gonna break through. So they're clearly gonna be getting customers the buyer side, how should they be looking through the lens right now and looking at companies, what should they look for? Um, and they like to take chances with seeing that. So it's not so much, they gotta be vetted, but you know, how do they know the winners from the pretenders? >>You know, I, I think the customers are always smart. I think in the, in the, in the past in market market tech, especially they often had a budget to experiment with. I think you're looking now the customers, the buyer technologies are looking for a hard ROI, like a return on investment. And before think they might experiment more, but now they're saying, Hey, are you gonna help me save money or increase revenue or some hardcore metric that they care about? So I think, um, the startups that actually have a strong ROI, like save money or increased revenue and can like point empirically how they do that will, will, you know, rise to the top of, of the MarTech landscape. And customers will see that they're they're, the customers are smart, right? They're savvy buyers. They, they, they, they, they can smell good from bad and they're gonna see the strong >>ROI. Yeah. And the other thing too, I like to point out, I'd love to get your reaction real quick is a lot of the companies have DNA, any open source or they have some community track record where communities now, part of the vetting. I mean, are they real good people? >>Yeah. I, I think open stores, like you said, in the community in general, like especially all these communities that move on slack or discord or something else. Right. I think for sure, just going through all those forums, slack communities or discord communities, you can see what's a good product versus next versus bad. Don't go to like the other sites. These communities would tell you who's working. >>Well, we got a discord channel on the cube now had 14,000 members. Now it's down to six, losing people left and right. We need a moderator, um, to get on. If you know anyone on discord, anyone watching wants to volunteer to be the cube discord, moderator. Uh, we could use some help there. Love discord. Uh, Jerry. Great to see you. Thanks for coming on. What's new at Greylock. What's some of the things happening. Give a quick plug for the firm. When you guys working on, I know there's been some cool things happening, new investments, people moving. >>Yeah. Look we're we're Greylock partners, seed series a firm. I focus at enterprise software. I have a team with me that also does consumer investing as well as crypto investing like all firms. So, but we're we're seed series a occasionally later stage growth. So if you're interested, uh, FA me@jkontwitterorjgreylock.com. Thank you, John. >>Great stuff, Jerry. Thanks for coming on. This is the Cube's presentation of the, a startup showcase. MarTech is the series this time, emerging cloud scale customer experience where the integration and the data matters. This is season two, episode three of the ongoing series covering the hottest cloud startups from the ADWS ecosystem. Um, John farrier, thanks for watching.

>>Welcome everyone to the cubes coverage of women in data science conference width 2022. Live from Stanford at the Arriaga alumni center. I'm Lisa Martin. My next guest is joined me. Sharon Hutchins is here the VP and chief of AI plus data operations at Intuit Sharon. Welcome. Thank you. >>Excited to >>Be here. This is your first woods, very first but into it in words. >>That's right. Intuitively it's goes way back. I'm relatively new to the organization, but Intuit has been a long time sponsor of woods, and we love this organization. We have a great alignment with our goals, which has a passion and commitment to advancing women in technology and data science. And we have the same goal added to it. We are at 30% women in technology with the goal of hitting 37% by 2024. And I know that widths has a great goal of 30 by 30, so that's awesome. >>30 by 30. And here we are around, I think it's still less than 25% of stem positions are filled by women. But obviously you're ahead of that on Intuit congratulate. >>I think we're ahead of that. And I think part of the reason why we're ahead of that is because we've got great programs at Intuit to support women. One of our key programs is tech women at Intuit. And so it's an internal initiative where we focus on attracting, retaining and advancing women. So it's a great way for women across technology to support one another. Sure. You've heard of the term there's power in the pack, and we believe that when we connect women, we can help elevate their voices, which elevates our business and elevates our products. >>It does. In fact, there's some stats I was looking at recently that just showed if there was even 30% females at the executive level, how much more profitable organizations can be in how much higher performance they can have. So the data is there that suggests this is a really smart business decision to be making. >>Absolutely absolutely the data is, is no lie. I see it firsthand in my own business. And in fact, at Intuit, we've got a broader initiative around diversity and inclusion. It's led from the top. We have set goals across the company and we hold ourselves accountable because we know that if there are more women at the table and more diversity at the table, all around, we make better business decisions. And if you look at our product suite, which is a terrible tax, QuickBooks, mint, credit, karma, and MailChimp, we've got a diverse customer base of a hundred thousand, sorry, a hundred million customers. And so it's a lot of diversity in our customer base and we want a lot of diversity in the company. >>Fantastic. That there's such a dedicated effort to it. You just came in here from the career panel. Talk to me about that. What were some of the key things that were discussed? Yeah, >>I have my notebook open here because there were so many great takeaways from actually just from the day in general. I'm just so at, at the types of issues that women are tackling across different industries, they're tackling bias. And we know that bias is corrected when women are at the table, but from a career perspective, some of the things that were mentioned from the panel is the fact that women need to own their own careers and they need to actively manage their careers. And there's only so much your manager can do and should do. You've got to be in the driver's seat, driving your own career. One of the things that we've done at Intuit as we've implemented sort of a self promoting process. So twice a year during our promotion period, either your manager can nominate you for a promotion or you can self promote. So it's all about you creating a portfolio of all of your great work. And of course, you know, managers are very supportive of the process and support, you know, women and, and all technologists in crafting their portfolios for a fair chance at promotion. And so we just believe that if you take bias out of a career progression, you can close that fair and equitable gap that we see sometimes across industries with compensation. >>This is, that would be great if we can ever get there. One of the things that's nice about woods, I think it was last year or the year before they opened it up to high school students. So it was so nice walking in this morning, seeing the young, fresh faces, the mature faces, but you bring up a great point of women need to be their own mini to create their own personal board of directors and really be able to, to be at the helm of their career. Do you, did you find that the audience is receptive to that? Do they have the confidence to be able to do that? >>Yeah, absolutely. And, and that was a point that was raised a couple of times this morning, there were women who talked about having great mentors, but it is more important to have a board of your personal board of directors than one mentor, because you've got to make sure that you sort of tackle all aspects of your career life. And you know, it's not all about the technology, a good portion of how you spend your time and where you spend your time is collaborating and negotiating and communicating across the company. And so that's very important. And so that was a key message that folks shared this morning. >>That's good. That's incredibly important. I wish we had more time. You've got to run to the airport. Sharon, it's been a pleasure to have you on the program. Thank you for sharing what Intuit and woods are doing together, your involvement and some of the great messages, inspiring messages from the career panel. >>Exactly. And for all of the young expiring high school students. Yes. We want them to check out into it. www.intuit.com, careers, >>Intuit.com. Is it slash careers slash careers slash careers perfectly. I'm an Intuit customer. I will say. Awesome. It's been a pleasure talking to you. Thank you, Sharon. Bye-bye for Sharon Hutchins. I'm Lisa Martin. You're watching the cubes coverage of women in data science, 2022.

hi everybody we are live at AWS reinvents in Las Vegas I'm Jeff Kelly with Wikibon org you're watching the cube silicon angles premiere live broadcast we go out to the technology events and as John foyer likes to say extract the signal from the noise so being here at the AWS show we were talk we're going to talk to a lot of AWS customers here a lot about what they're doing in in this case around analytics data warehousing and data integration so for this segment I'm joined by two customers Daniel heacock senior business systems analyst with a tix and Adam Cain's who's a data architect with federated sample welcome guys thanks for joining us on the cube Thanks your first time so we'll promise we'll make this as painless as possible so so you guys have a couple things in common we were talking beforehand some of the workflows are similar you work your you're using Amazon Web Services redshift platform for data warehousing you're using attunity for some of the data integration to bring that in from your for your operational transactional databases and using a bi tool on top to kind of tease out some of the insights from that data but why don't we get started Daniel we'll start with you tell us a little bit about etix kind of what you guys do and then we'll just kind of get into the use cases and talk to use AWS and the tuner need some of the other technologies you use it sure yeah so the company I work for is etix we are a primary market ticketing company in the entertainment industry we provide a box office solutions to venues and venue owners all types of events casinos fairs festivals pretty much you name and we sell some tickets in that industry we we provide a software solution that enables those menu owners to engage their customers and sell tickets so could kind of a competitor to something like ticketmaster the behemoth in the industry and you're definitely so Ticketmaster would be the behemoth in the industry and we are we consider ourselves a smaller sexier version that more friendly to the customer customer friendly more agile absolutely so Adam tell us a little bit about better a sample sure federated sample is a technology company in the market research industry and we aim to do is add an exchange layer between buyers and sellers so we facilitate the transaction between when a buyer or a company like coke would say hey we need to do a survey we will negotiate pricing and route our respondents to their surveys try to make that a more seamless process so they don't have to go out and find your very respond right everything online and right right absolutely got it so so let's talk a little bit about let's start with AWS so obviously we're here to reinvent a big show 9,000 people here so you guys you know talk about agile talk about cloud enabling kind of innovation and I'm gonna start with you what kind of brought you to AWS are you using red shift and I think you mentioned you're all in the cloud right just give us your impressions of the show in AWS and what that's meant your business right shows been great so far as to we were originally on-premise entirely at data center out in California and it just didn't meet our rapid growth we're a smaller company startup so we couldn't handle the growth so we need something more elastic more agile so we ended up moving our entire infrastructure into amazon web services so then we found that we had a need to actually perform analytics on that data and that's when we started the transition to you know redshift and so the idea being you're moving data from your transactional system which is also on AWS into redshift so using attunity for that they're clapping solution talk a little bit about that and and you know how that is differentiate from some of the other integration methods you could have chosen right so we started with a more conventional integration method a homegrown solution to move our data from our production sequel server into redshift and it worked but it was not optimal didn't have all the bells and whistles and it was prone to bad management being like not many people could configure it know how to use it so then we saw cloud being from attunity and they offered a native solution using secret survey replication that could tie into our native sequel server and then push that data directly into cloud being at a very fast rate so moving that data from from the sequel server it is essentially a real-time replication so that yes that's moving that data into redshifts of the year analysts can actually write when they're doing there the reporting or doing some real ad hoc kind of queries they can be confident they've got the most up-to-date data from your secret service right actual system right yeah nearly real-time and just to put in perspective the reports that we were running on our other system we're taking you know 10 15 minutes to run in redshift we're running those same reports in minutes 1 12 minutes right and if you're running those reports so quickly you know the people sometimes forget when you're talking about you know real time or interactive queries and reporting it's somewhat only as good as the data timeliness that you've got that you by Dave the timeless of the data you've got in that database because right trying to make some real-time decisions you've got a lag of depending on the workload and your use case even 15 minutes to an hour back might really impact you're ready to make those decisions so Adam talk a little bit about your use case is it is a similar cloud cloud architecture are you moving from upside Daniel moving from on-premise to so you're actually working with an on-premise data center it's an Oracle database and so we've basically we we ran into two limitations one regarding to our current reporting infrastructure and then to kind of our business intelligence capabilities and so as an analyst I've been kind of tasked with creating internal feedback loops within our organization as far as delivering certain types of KPIs and metrics to you know inform our our different teams or operations teams our marketing teams so that has been one of the kind of BI lms that we've been able to achieve because of the replication and the redshift and then the the other is actually making our reporting more I guess comprehensive we're able to run now that we're using redshift we're able to run reports that we were previously not be able to do to run on our on-premise transactional database so really we just are kind of embracing the power of redshift and it's enabling us and a lot of different types of ways yeah i mean we're hearing a lot about red shift at the show it's the amazon says the fastest-growing service AWS has had from a revenue perspective and it's six seven year history so clearly there's a lot of power in that platform it removes a lot of the concerns around having to manage that infrastructure obviously but the performance you know that's that's something I think when people are have their own data centers their own databases tuning those for the type of performance you're looking for is can be a challenge is that one of the drivers to kind of your move to redshift oh for sure the performance i I'm trying to think of a good example of a metric to compare but it's basically enabled us to develop a product or to develop products that would not have been possible otherwise there were certain i guess the ability to crunch data like you said in a specific time frame is very important for reporting purposes and if you're not able to meet a certain time frame then certain type of report is just not going to be useful so it's opening the door for new types of products within our organization well let's dig into that a little bit the different data types we're talking about so you've got a tea tix you're talking about customer transactions your custom are you talking about profiles of different types of customers tell us about some of the data sources that you're moving from your transactional system which i think is an Oracle database to to red shift and then you know what are some of those types of analytic workloads what kind of insights are you looking for sure so you know we're in the business of selling tickets and so one of our you know main concerns or I guess you should say we're in the business of helping our customers sell tickets and so we're always trying to figure out ways to improve their marketing efforts and so marketing segmentation is one of the huge ones appending data from large data services in order to get customer demographic information is something as you know easy to do in red shift and so we're able to use that information transaction information customer information I guess better engage our fans and likewise Adam could you maybe walk us through kind of a use case maybe your types of data you're looking at right that you're moving into red ship with attunity and then you know what kind of analytics are you doing on top of that what kind of insights are you gathering right so are our date is a little bit different than then ticketing but what we ultimately capture is is a respondent answers to questions so we try to find the value in a particular set of answers so we can determine the quality of the supply that's sent from suppliers so if they say that a person meets a certain demographic that we can actually verify that that person reads that demographic and then we can actually help them improve their supply that they push down to that respondent to it everybody makes more money because the completion rates go up so overall just business and analysis on that type of information so that we can help our customers and help ourselves so I wonder if we could talk a little bit about kind of the BI layer on top as well I think you're both using jaspersoft but you know beyond that you know one of the topics we've been covering on the cube another and on Wikibon is this whole analytics for all movement and we've been hearing about self service business intelligence for 20-plus years from some of the more incumbent vendors like business objects and cognos that others but really I mean if you look at a typical enterprise business intelligence usage or adoption rate kind of stalls out by eighteen percent twenty percent talk about how you've seen this kind of industry evolve a little bit maybe talk about jaspersoft specifically but what are some of the things that you think have to happen or some of the types of tools that are needed to really make business intelligence more consumable for analysts and more business use people who are not necessarily trained in statistics aren't data scientists Adam we start yes so one of the things that we're doing is with our jaspersoft we're trying to figure out you know certain we have a pis and we have traditional you know client server applications which ones our customers want to use the most because we're trying to push everybody towards an API oriented so we're trying to put that data into redshift with Jasper soft and kind of flip that data and look at it year-to-date or over a period of time to see where all of our money's coming from where others are rather than getting driven from and our business users are now empowered with jaspersoft to do that themselves they don't rely on us to pull data from they could just tie right into jaspersoft grab the data they need for whatever period of time they want and look at it in a nice pretty chart as a similar experience you're having any text definitely and I think one of the things I should emphasize about our use of Jasper's off and basically really any bi tool you choose to use in the Amazon platform is just the ability to launch it almost immediately and be able to play with data within 5-10 minutes of trying to launch it yeah it's pretty amazing what how quickly things can come from just a thought into action so well that's a good point because I mean you think about not just bitten telligence but the whole datawarehousing world it was you know the traditional method is you you know the business user a business unit goes to IT they say here are some of the requirements of the metrics we want on these reports IT then gun it goes away and builds it comes back six months later 12 months later here you go here's the report and next thing you know the business doesn't remember what they asked for this isn't necessarily going to serve our needs anymore and you've just essentially it's not a particularly useful model and Amazon really helps you kind of shorten that time frame significantly it sounds like between what you can do with redshift and some of their other database products and whatever bi to used to use is that kind of how you see this evolving oh definitely and the options I guess the the kind of plug and play workflow is is pretty pretty amazing and it's a it's given us the flexibility in our organization to be able to say well we can use this tool for now and there's a there's a chance we may decide there's something different in the future that we want to use and plugin in its place we're confident that that product will be there whenever the you know whenever the need is there right well that's the other thing you can you can start to use a tool and if it doesn't meet your need you can stop using it move to another tool so I think that puts you know vendors like jaspersoft than others puts them on their toes they've got to continually innovate and make their product useful otherwise you know they know that you know there were AWS customers can simply press the button stop using it press another button stop start using another tool so I think it's good in that sense but kind of you know when you talk about cloud and especially around data you get questions around privacy about data ownership who owns the data if it's in amazon's cloud is your data but you know it's on there in their data centers how do you feel about that Adam is there any concerns around either privacy or data ownership when it comes to using the cloud I mean you guys are all in in the cloud so right yeah so we've isolated a lot of our data into virtual private clouds so with that segment of the network we feel much more comfortable putting our data in a public space because we do feel like it's secure enough for our type of data so that was one of the major concerns up front but you know after talking with Amazon and going through the whole process of migrating to we kind of feel way more comfortable with that if you expand on that a little so you've got a private instance essentially in amazon's rep right so we have a private subnet so it's a segmented piece of their network that's just for us okay so we're not you can't access this publicly only within our VPN client or within our infrastructure itself so we're segmented we're away from that everybody else interesting so they offer that kind of type of service when there's more privacy concern as a security concern definitely and of course a lot depends on the type of data i mean how sensitive that data is if it you know but personally identifiable data obviously is going to be more sensitive than if it's just a general market data that anyone could potentially access daniel is we'll talk about your concerns around that or did you have concerns definitely a more of a governance people process question than a technology question I think well I definitely a technology question to a certain extent I mean as a as a transaction based business we were obviously very concerned with security and our CTO is very adamant about that and so that was one of the first first issues that we address whenever we decided to go this route and I'm obviously AWS has has taken all the precautions we have a very similar set up to what Adam is describing as far as our security we are very much confident that it is a very robust solution so looking forward how do you see your use of both the cloud and kind of analytics evolving you know one of the things we've been covering a lot is the as use case to get more complex your kind of you've got to orchestrate more data flows you've got to move data for more places you mentioned you're using attunity to do some of that replication from your transactional database and some red shift you know what are some of the other potential data integration challenges you see fate you see yourselves facing as you kind of potentially get more complex deployments we've got more data maybe you start using more services on Amazon how do you look to tackle some of those eight integration challenges let me start that's a good question one of the things we're trying to do inside of you know our organization is I guess bring data from all the different sources that we have together we have you know we use Salesforce for our sales team we collect information from MailChimp from our digital marketing agency that that we'd like to tile that information together and so that's something we're working on attunity has been a great help there and they're you know they're their product development as far as their capabilities of bringing in information from other sources is growing so that's a you know we're confident that the demand is there and that the product will develop as we as we move forward well I mean it's interesting that we've got you know you two gentlemen up here one with a kind of a on premise to cloud deployment and one all in the cloud so I'm clearly tuning you can kind of gap both those right on premise and cloud roll but also work in the cloud environment Adam when we if you could talk a little bit about how you see this kind of evolving as you get more complex maybe bring in more systems are you looking to bring in more data sources maybe even third-party data sources outside data sources how are you how do you look at this evolve right President Lee we do have a Mongo database so we have other sources that we're doing now there's talks of even trying to stick that in dynamo DB which is a reg amazon offering and that ties directly into redshift so we could load that data directly into that using that key pair or however we want to use that type of data data Mart but one of the things that we're trying to work out right now is just distribution and you know being agile you know elasticity which I work those issues with our growing database so so our database grows rather large each month so working on scalability is our primary focus but other data sources so we look into other database technologies that we can leverage in addition to sequel server to help distribute that load you so we've got time just for one more question I wonder I always like to ask when we get customers and users on if you can give some advice to other practitioners for watching so I mean if you can give one piece of advice to somebody who might be in your position they're looking at maybe they've got an on-premise data warehouse or maybe they're just trying to figure out a way to to get make better use of their data I mean what would the we the one thing would it be a technology piece of advice maybe you know looked at something like red shift or and solutions like attunity but maybe it would be more of a you know cultural question around the use of data and I'm I instead of making data-driven decisions but with that kind of one piece of ice big I could put you on the spot okay I would say don't try to do it yourself when the experts have done it for I couldn't put it any more simpler than that very succinct but very powerful but for me my biggest takeaway would be just redshift I was kind of apprehensive to use it at first I was so used to other technologies but we can do so much with redshift now add you know half the cost so your good works pretty compelling all right fantastic well Adam pains Daniel heacock thank you so much for joining us on the cube appreciate it we'll be right back with 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